CSV Sentiment Analysis

Integer value calculated by summing the valence of each sentiment-bearing word. Higher positive numbers indicate stronger positive sentiment, negative numbers indicate negative sentiment. Example: "love" = +3, "hate" = -3.

Normalized score between -1 and 1, calculated by dividing the raw score by the number of words. Useful for comparing texts of different lengths. Values above 0.05 are typically positive, below -0.05 are negative, and between are neutral.

Simple categorical classification based on the comparative score. Positive if comparative > 0.05, Negative if < -0.05, otherwise Neutral. This provides an easy-to-understand sentiment label.

Number of positive and negative words detected in the text. Helps understand the balance of sentiment-bearing words. Example: "I love this but hate that" has 1 positive word and 1 negative word.

Comma-separated list of words that contributed to the sentiment score. Useful for understanding which specific words influenced the analysis. Includes both positive and negative sentiment words.